Fecal sample and/or breath sample analysis for treating inflammatory bowel disease and related conditions

ABSTRACT

The invention is related to a system for treating irritable bowel syndrome, Crohn&#39;s disease, ulcerative colitis (collectively, inflammatory bowel disease, or “IBD”) by determining a number of indicators, including genetic markers, gene expression levels, levels of certain compounds in the gut or feces, hydrogen and/or methane levels, and concentrations of particular bacteria in the gut or feces, and correlating one or more such indicators with symptoms in test subjects with IBD; and correlating diet, drugs, supplements or other therapy, with alleviation of IBD symptoms. The correlations established in the test subjects are confirmed or refuted for individuals suffering IBD, and the treatments established as reducing symptoms are supported through messaging and compliance is verified by monitoring the indicators.

BACKGROUND OF THE INVENTION

As much as 74% of the American population experiences various digestiveproblems and/or conditions. Chronic digestive diseases (such as celiacdisease, Crohns disease, irritable bowel syndrome, or ulcerativecolitis) affect at least 70 million people. Furthermore, up to 37% ofpatients with chronic digestive disease are admitted into an emergencyroom every year and 70% of such patients need some type of surgicalintervention.

Making wise dietary choices can be confusing, particularly if certainfoods, stress, and/or exercise exacerbate the problem. For individualswith chronic digestive complications or discomfort making everyday foodchoices, can be confusing, unpredictable, and often embarrassing (in thecase of inadvertent public gas or stool discharge). Medical regimens toaddress these diseases and assist in relieving symptoms are complicatedand involve complicated medication regimens that are difficult andexpensive to manage. Changes in diet can ameliorate or sometimes eveneliminate the symptoms of these conditions. Methane and hydrogenproduction can be used as markers to determine the effect of dietarychanges on symptoms. Symptom relief has been achieved with a low-FODMAPdiet (low in fermentable sugars) in a large majority of functionalgastrointestinal disorders patients with fructose or lactoseintolerance. Wilder-Smith et al., “Predictors of response to alow-FODMAP diet in patients with functional gastrointestinal disordersand lactose or fructose intolerance.” Aliment Pharmacol Ther 2017 April;45(8):1094-1106.

Animal model experiments have shown that methane, a gaseous by-productof intestinal bacteria, slows small intestinal transit and appears to doso by augmenting small bowel contractile activity. Pimentel M, et al.,“Methane, a gas produced by enteric bacteria, slows intestinal transitand augments small intestinal contractile activity.” Am J PhysiolGastrointest Liver Physiol 2006; 290: G1089-95. In the lactulose breathtest (where the patient is challenged with lactulose and then methaneproduction is measured), methane in the breath of IBS patients has beenassociated with severity of constipation. Chatterjee S, “The degree ofbreath methane production in IBS correlates with the severity ofconstipation.” Am J Gastroenterol 2007; 102: 837-41. Elevated hydrogenproduction, as measured in the breath, is also widely believed to beassociated with symptoms in inflammatory bowel disease.

The levels of certain volatile organic metabolites in the feces ofpatients with diarrhea- predominant IBS (IBS-D), active Crohn's disease(CD), ulcerative colitis (UC) (collectively, inflammatory bowel disease,or “IBD”) and healthy controls are indicators of IBD. Ahmed, I. et al.“An Investigation of Fecal Volatile Organic Metabolites in IrritableBowel Syndrome,” PLoS One. 2013; 8(3): e58204. These researchers arrivedat a list of 28 such volatile metabolites associated with IBS and nothealthy controls, and a list of 11 such volatile metabolites associatedwith healthy controls and not with IBS.

TABLE A No. Compounds  1 Butanoic acid, ethyl ester  2 Propanoic acid,methyl ester  3 1-Methyl-2-(1-methylethyl)-benzene  4 Butanoic acid,butyl ester  5 Butanoic acid, propyl ester  6 Hexanoic acid, methylester  7 Propanoic acid, propyl ester  8 Acetic acid, butyl ester  9Butanoic acid, 3-methyl-, butyl ester 10 Propanoic acid, butyl ester 11Cyclohexanecarboxylic acid, ethyl ester 12 Butanoic acid, 2-methyl-,propyl ester 13 Ethanoic acid, ethyl ester 14 Pentanoic acid, 4-methyl15 Acetic acid, pentyl ester 16 Pentanoic acid, butyl ester 17 Butanoicacid, 3-methyl, propyl ester 18 Cyclohexanecarboxylic acid, propyl ester19 6-Methyl-5-hepten-2-one 20 Propanoic acid, 3-methyl-butyl ester 21Ethanoic acid, 3-methyl-l-butyl ester 22 Cyclohexanecarboxylic acid,butyl ester 23 Benzoic acid, 2-hydroxy-, methyl ester 24 Pentanoic acid,4-methyl-, pentyl ester 25 Butanoic acid, 3-methyl-, methyl ester 26Thiopivalic acid 27 5-Methy1-2-(1-methylethyl)-cyclohexanone 284-Methyl-1-Indole

TABLE B  1 2-Heptanone  2 2-Methylpropanal  3 3-Methylbutanoic acid  4Undecane  5 3-Methylbutanal  6 2-Methylpropanoic acid  72-Methyl-l-propanol  8 1R-a-Pinene  9 2-Penhifizran 10Methoxy-phenyl-oxime 11 2-Methylfuran

These compounds could be detected in a fecal sample to indicate thepresence of IBD, or the likelihood that it is in remission or symptomshave alleviated (where the compounds in Table B predominate). Moreimportantly, they could be used to determine an appropriate diet foramelioration of IBD, by determining which foods cause increases ordecreases in these volatile metabolites, first in a group of testsubjects using AI/software agents to find the optimal foods, then ineach individual who would be a participant, who could be monitored forthese metabolites, and would report their diet on a regular basis. Withthat information for the individual the software agent would determinethe optimal diet to ameliorate IBD for the individual.

SUMMARY OF THE INVENTION

The invention includes finding correlations, in patient feces, betweencertain genetic markers indicative of mutant subspecies of the bacteriain the gut, certain levels of gene expression, certain levels ofvolatile organic compounds (VOCs) and certain levels of methane andhydrogen in patient breath (or feces), certain levels of gut bacteriamaking up the microbiome; and negative symptomology (“Events”), asdetermined in a group of test subjects. It further includes findingfoods which prevent, reduce incidence of or otherwise ameliorate Events,and finding in test subjects correlations between consuming such foodsand levels (i) of volatile organic compounds (VOCs) in patient feces,and levels (ii) of methane and hydrogen in patient breath (or feces),and optionally, (iii) microbiome composition (including as determinedfrom fecal genetic markers indicating mutants or wild type, analyzed byeither DNA or 16 S RNA analysis), or (iv) gene expression; so thatlevels (i), (ii), (iii) and/or (iv) can serve as indicators of a dietwhich reduces Events. As a further step, the molecular-level microbiomeanalysis can identify changes in gut bacteria over time, and correlatethose changes with changes in levels (i) or (ii) above, and with symptomrelief. Thus, mutant bacteria associated with symptoms can be identifiedfrom fecal samples.

It further includes finding a diet which ameliorates Events in testsubjects with genetic markers or levels of gene expression correlatedwith IBD; and then applying that diet to participants with the samemarkers or gene expression levels.

After finding such an optimal diet for the test subjects, the diet istried in an individual, and changed as necessary to reduce Events and/orchange levels (i), (ii), (iii) and/or (iv) to more desirable levels—withthe goal being to prevent, reduce incidence of or ameliorate Events inthe individual.

Test subjects and participants send in fecal samples preferablycollected with a collection system as outlined in FIGS. 1-4C; orotherwise, for testing for levels (i), (ii), (iii) and/or (iv). Forpreferably determining levels of (ii), test subjects and participantsperiodically measure methane and hydrogen in the breath, using awireless device which sends the results to a server. See e.g., U.S.Publ'n No. 20180271404 (disclosing a methane and hydrogen sensor forbreath, to integrate with a smartphone or other device). Test subjectsand participants report their symptoms and food intake, preferably usinga wireless device which sends the results to the server. Alternatively,the off-gassed methane and hydrogen in a fecal sample can be measured.

The server includes software agents which analyze the input from testsubjects and participants against a profile they initially provided, andsends messages regarding foods to avoid or preferentially consume, basedon all the available information. The software agents preferably monitorthe effect of particular messages on particular test subjects orparticipants, in terms of moving their food consumption to one which ismore preferred, and sends the more effective messages going forward tothose. The server preferentially also determines if participants areaccurately reporting their food consumption, by monitoring the reportedfood consumption against levels (i), (ii), (iii) and/or (iv), anddetermining if there is the predicted correlation. If the predictedcorrelation is lacking, the participant is assumed to not be accuratelyreporting food consumption; and can be sent a message to report moreaccurately.

Fecal samples must be initially monitored for markers and geneexpression levels, and baseline VOCs. Initial breath samples aremonitored for methane and hydrogen levels. Fecal samples are thenperiodically monitored for changes to genetic markers, gene expressionlevels, baseline VOCs, and breath samples are periodically monitored formethane and hydrogen levels. A preferred sample collection systemincludes a disposable feces catcher to place below the toilet seat, anda sealed, pre-addressed sample collection tube, which has a self-sealingcap through which a probe with sample adhered at one end, is pushed intothe interior of the tube.

An alternative fecal sample container has a multi-chamber design and canbe used to determine the quantity of hydrogen and/or methane from afecal sample, instead of or in addition to the measurement of hydrogenand/or methane from the subject's breath. In this alternative, arelatively standard amount of fecal material is placed in the containerand the off gas is collected—preferably in a chamber of the same samplecontainer. The off gas can also be analyzed to determine the levels ofVOCs in the fecal sample.

The foregoing has outlined rather broadly several aspects of the presentinvention in order that the detailed description that follows may bebetter understood.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an exploded view of components of a fecal sample container andother components of a fecal sampling kit.

FIG. 2 is an assembled fecal sample container of the components shown inFIG. 1, with a fecal sample outside.

FIG. 3A is a sectional view of the upper part of the assembled fecalsample container taken along a vertical plane with the fecal port andport control in closed position and the lower gate in chamber 106closed.

FIG. 3B is a sectional view of the upper part of the assembled fecalsample container taken along a vertical plane with the fecal port andport control in closed position and the lower gate in chamber 106 open.

FIG. 3C is a sectional view of the upper part of the assembled fecalsample container taken along a vertical plane with the fecal port andport control in open position and the lower gate in chamber 106 closed.

FIG. 4A is a sectional view of the fecal sample container taken along avertical plane with the fecal port and port control in open position andthe lower gate in chamber 106 closed.

FIG. 4B is a sectional view of the fecal sample container taken along avertical plane with the fecal port and port control in closed position,a fecal sample in place in chamber 106, and the lower gate in chamber106 closed.

FIG. 4C is a sectional view of the fecal sample container taken along avertical plane with the fecal port and port control in closed position,and the lower gate in chamber 106 open, allowing the fecal sample tofall into the tube 101.

FIG. 5A, 5B are two successive pages of a flow chart showing a methodfor determining correlations between (independent variables) certaingenetic markers, gene expression levels, volatile organic compoundlevels, and hydrogen and methane levels in the breath (or feces), toboth adverse events and diet, for IBD patients. It further shows how toconfirm the correlation for an individual with IBD, and messaging thatindividual to adhere to a recommended diet, and optionally, messagingthe individual to report the diet accurately (if the data and analysisindicates it is not reported accurately).

FIG. 6A, 6B show the equations representative of some of the steps inFIG. 5A, 5B.

FIG. 7A, 7B are two successive pages of a flow chart showing fecalsample testing for generating preferred gut bacterialcomposition/microbiome with a low nonpreferred foods and/or low FODMAPdiet.

For a more complete understanding of the present invention, and theadvantages thereof, reference is now made to the following descriptionin conjunction with the accompanying drawings, outlined above. stop

DETAILED DESCRIPTION

The use of the terms “a,” “an,” “the,” and similar referents in thecontext of describing the presently claimed invention (especially in thecontext of the claims) are to be construed to cover both the singularand the plural, unless otherwise indicated herein or clearlycontradicted by context.

Recitation of ranges of values herein are merely intended to serve as ashorthand method of referring individually to each separate valuefalling within the range, unless otherwise indicated herein, and eachseparate value is incorporated into the specification as if it wereindividually recited herein.

Use of the term “about” is intended to describe values either above orbelow the stated value in a range of approx. +/−10%; in otherembodiments the values may range in Value either above or below thestated value in a range of approx. +/−5%; in other embodiments thevalues may range in value either above or below the stated value in arange of approx. +/−2%; in other embodiments the values may range invalue either above or below the stated value in a range of approx.+/−1%. The preceding ranges are intended to be made clear by context,and no further limitation is implied. All methods described herein canbe performed in any suitable order unless otherwise indicated herein orotherwise clearly contradicted by context. The use of any and allexamples, or exemplary language (e.g., “such as”) provided herein, isintended merely to better illuminate the invention and does not pose alimitation on the scope of the invention unless otherwise claimed. Nolanguage in the specification should be construed as indicating anynon-claimed element as essential to the practice of the invention.

As used herein, the term “comprising,” when utilized, means “including,but not necessarily limited to”; it specifically indicates open-endedinclusion or membership in the so-described combination, group, seriesand the like.

It is to be understood that the disclosed embodiments are merelyexemplary of the invention, which may be embodied in various forms.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a representativebasis for teaching one skilled in the art to variously employ thepresent invention in any appropriately detailed structure.

Embodiments of the invention are related to a system providing ahydrogen and/or methane sensor device and a wireless platform incommunication with the sensor device to periodically analyze thehydrogen and/or methane off gassing of an IBD subject's breath (or fromfeces) and correlating the levels of hydrogen and/or methane withsymptoms or Events.

Referring to FIG. 1, it shows a fecal sampling kit 100 with a spatula 50and a fecal sample container 101. Spatula 50 can be used by the subjectto scoop a small measured amount of fecal matter into chamber 106. Asnoted in the Summary, hydrogen and/or methane is preferentially measuredfrom the subject's breath, using a device as described in U.S. Publ'nNo. 20180271404. But it could also be measured from a fecal sample,where a relatively standard volume of fecal material 52 is placed inchamber 106, and the off gassed hydrogen or methane is measured.

Referring to FIGS. 3A to 4C, fecal sample container 101 has a threadedcap 102 with two chambers, 104, 106, each of which is sealed but can beaccessed by spatula, 50, carrying a solid, like fecal sample 52. Upperchamber 104 is sealed from the environment and capable of collectinggases from a sample 52 in the cap's lower chamber 106. The lower trapdoor of the lower chamber 106 is opened by e.g., twisting the cap 102 toallow sample 52 therein to fall into container 101. An automatic timer225 in cap 102 is activated by a sensor, which detects when the port onthe side of chamber 106 is opened for the sample to enter. The automatictimer 225 is preferably set to limit the gas measurement by a gas sensor(now shown) for a specific period of time (e.g., 10 seconds, 20seconds). Several off gassed hydrogen/methane measurements are taken insuccession and stored as individual values specific for a particularfecal sample of the individual subject. In one embodiment, allmeasurement values and related subject information for a specific fecalsample are recorded and then transferred to a data processor, preferablywirelessly, such as by Bluetooth to a mobile phone or other wirelessdevice. One preferred method for measuring the hydrogen/methane in afecal sample, is to include a tube running from upper chamber 104 anddetachably connecting to the breath sampler device (as described in U.S.Publ'n No. 20180271404), which then measures the levels ofhydrogen/methane in the fecal sample from the gas level in chamber 104.

After cap 102 is manipulated to open the lower chamber 106, the lowertrap door in chamber 106 opens and fecal sample 52 falls into container101. Cap 102 is twisted again to seal sample 52 in container 101.Container 101 is then shipped for fecal sample analysis and/oroptionally methane and hydrogen gas analysis, or, optionally VOCanalysis, of the gas collected in the upper chamber 104. Optionally thefecal sampling kit 100 may also contain a sealable impermeablepre-addressed bag that the fecal sample container 101 is placed into formailing to a laboratory for analysis. The fecal sample 52 analysis canbe for levels of the compounds in Tables A and B above, genetic markersassociated with IBD, levels of gene expression correlating with IBD, andthe bacterial composition of the sample.

A personalized database for subjects is created by capturing data frommultiple sources, including medical records such as their medicalhistory, laboratory data, diagnoses, treatment plans, and family medicalhistory. Another example of such data is data measured by one or morebiodata or sensor devices. Biodata can be collected by devices equippedwith the necessary software to process the data generated by the deviceand to communicate the collected data to the personalized database andfrom there, to a processor. Examples of such biodata-collecting devicesinclude glucometers, hydrogen or methane sensors, temperature sensors,heart rate monitors, blood pressure monitors, and activity sensors withtri-axis or multi-axis accelerometer chips.

The personalized database will also include input from extensivequestionnaires and individualized insights gained by understanding thesubject's social structure, daily routines and cultural background toassist in understanding how that person copes with a chronic conditionor symptoms on a daily basis. This type of data is vital to findingpersonalized treatment plans that a person will adhere to and that willprovide positive changes in a person's quality of life. Although peopleshare the same disease or the same chronic symptomology, their abilityto navigate through the symptoms often will include personal adjustmentsto their daily routines. Many people facing chronic diseases andassociated uncomfortable or embarrassing symptoms will try alternativeapproaches that they are unwilling to share with their physicians. Thus,a great deal of relevant information does not appear in their medicalrecords. Often these alternative approaches will include herbalremedies, supplements, acupuncture or acupressure, reflexology,relaxation techniques, or exercise regimes such as yoga or stretching.

A processor stores a number of software applications and agentsexecutable by the processing unit. The software applications and agentsinclude a data extraction and analysis application that extracts,identifies and links associated processed data acquired from varioussources. The data extraction applications include inference engines andother algorithmically based applications used to identify and correlaterelevant information in a personalized database and external datasources. The processor, through agents and applications, is capable ofperforming all the operations described in the flowcharts in FIGS. 5A to7B.

In one embodiment, the processor can include a processing unit having amultitude of interrelated elements. Embodiments of the processing unitcan be implemented to some extent as software modules installed andrunning on one or more processing systems, such as servers,workstations, tablet computers, PCs, and so on. The processor generallyincludes a knowledge module that derives further knowledge orinformational data from existing knowledge using inference, analysis,crowd sourced wisdom and continuous monitoring data from a personalizeddatabase of the subject.

Thus, the knowledge module is a “care” analysis engine that stores itsdata in the data repository. The data repository can include one or moredatabases that communicate with the knowledge module. The knowledgemodule can also receive data from an external data sourced database. Theexternal sourced database may include data from various sources, such aslaboratories, insurance companies, hospitals/clinics. media companies,24/7 call centers/caregivers, account administrators, and other sources.The data from the external database can be extracted and transferred tothe knowledge module using dynamic APIs.

The processor processes information accessed and derived by theknowledge module to determine personalized clinical and nutritionaldecision analytics for subjects or individual system participants. Theprocessor may include one or more algorithms that provide both contentand personalized rules to provide feedback to the user in real time. Forexample, the processor may include code for predicting trends based uponthe subject's personalized health profile and preferences. Theinformation acquired from a subject's personalized data input by thesubject and data derived from an analysis of subject samples may bestored in the data repository and accessed by the processor.

The data extraction applications on the processor identify, analyze andcorrelate relevant information in the personalized database and datacontinuously gathered, including hydrogen and methane levels (sourcedfrom breath or fecal off-gas), the genetic marker and/or gene expressionanalysis, the analysis of the VOCs in patient feces; and, as input bythe subject: the diet and foods consumed and the adverse events(symptoms of IBD). See FIGS. 5A-6B. The data continuously gathered canalso include gut bacterial composition. See FIGS. 7A, 7B.

The processor includes applications/agents which, based on the analysisof the personalized database and the data continuously gathered, sendmessages to subjects regarding food consumption; particularly, how tobetter conform to a low FODMAP or other preferred diet. The processormay also message daily meal, an activity plan or exercise plan for thesubject, recommendation to contacting a coach or health guide (a HealthSherpa), nutritional guidance, subject reports and predictions, subjecthealth profiles and videos or chat sessions.

Typically, the processor will include code for predicting trends basedupon the individual subject's personalized health profile andpreferences. For example, the rules may pertain to a daily meal oractivity plan for the participant based on personal preferences, amatching of the subject to one or more health consultants, nutritionguidance, exercise routines, general health predictions and alerts,trends and improvements in the subject's health profile and video/chatsessions. Various parameters are considered in determiningrecommendations, educational messages, and directives to the subject.The processor analyzes and correlates the relevant data to determineuseful information for the specific subject and transmits thatinformation to the subject, including information relating to nutrition,exercise advice and treatment. Access privileges to any processorinformation may also be driven rules based on health care privacyregulations and laws.

A portal on the processor, which is preferably web-based, can beprovided by the processor. The portal can provide interfaces forreporting and displaying the data analyzed by the processor, andincluding information and recommendations for the subject or the healthcare personnel, or messaging for the subject. Portal access iscontrolled through established access privileges.

To use the care management system of the invention, the subject usesfecal sampling kit 100 and preferably, also a breath sampling unit. Thesubject will collect a fecal sample 52 using a spatula 50 and place itinto fecal sample container 101. The subject will then either follow theprocedure to use the cap system to measure hydrogen and methane from thesample, or use the breath sensor in the alternative. The gasmeasurements are then communicated to the processor, and the fecalsample container is sealed and sent for genetic and VOC analysis, andoptionally, for bacterial composition.

The processor's software agents analyzes and correlates all analysisincluding those input to the personalized database, to enhance theability of the care management system to provide updated and relevantguidance, through messaging to the subject. For example, the softwareagents will correlate changes in incidence of symptomatic events withlevels of methane and hydrogen, VOCs, genetic markers and geneexpression, as well as diet, and optionally, the feces bacterialcomposition. The specifics of these correlations and analysis areillustrated in FIGS. 5A-7B.

Another use for the analyses set forth in FIGS. 5A-7B, other thanoptimizing diet as illustrated, is to determine effectiveness and dosageof therapeutic drugs on the subject. The same analysis can be used asfor diet optimization, to find drugs and dosages which effectivelyreduce symptomatic events (“Events” in FIGS. 5A-7B).

Referring to FIGS. 5A, 5B, where the steps are shown in flow chart formwith limited explanation, the following steps 1 to 23 are acomprehensive explanation of the steps in the FIGS. 5A, 5B process.

1) Obtain details of digestive health of each test subject: healthprofiles, and past and present digestive ailments i.e.: whethersuffering from IBS, IBD, frequent diarrhea, high frequency flatulence,high frequency bowel movements (“Events” or “symptoms”), and also thebaseline frequency of Events (“Evsbaseline”);

2) Perform baseline fecal sample collection for test subjects toinitially determine: (i) DNA and/or RNA markers for wild type and mutantbeneficial or detrimental bacterial strains in the gut microbiome(“Markers1-x”); (ii) gene expression of any candidate genes (from theindividual or the microbiome bacteria) whose expression is elevated ordecreased in the test subjects from normal (“GeneExp1-x”); (iii) levelsof volatile organic compounds in Table A (“VOCsLvL1-x”) and in Table B(“B-VOCsLvL1-x”) associated with test subjects where the VOCsLvL andB-VOCsLvL can be measured from gas associated with the fecal sample; and(iv) determine from a breath sensor carried by test subjects the methane(“BrM”) and hydrogen levels (“BrH”) in each subjects' breath, where 1-xindicates a reading at a different time for methane and hydrogen levels,which can be transmitted to a server;

3) Monitor diet of each test subject using a wireless device whichallows input of all food items and quantity consumed; withrecommendations on screen for low FODMAP foods, and preferably showingcarbohydrate content and glycemic Index, fat and protein content, glutenlevels, for each meal or for each food item;

4) Monitor each test subject's frequency of Events using the wirelessdevice, which allows their entry and category;

5) Collect fecal samples at intervals for each test subject: and monitorchanges in Markers1-x; GeneExp1-x; VOCsLvL1-x; and B-VOCsLvL1-x;Optionally: BrM or BrH, preferably, determine the average of thereadings (“AvBrM” and “AvBrH”) during each collection period;(Optionally, monitor the methane (“M1-x”) and hydrogen levels (“H1-x”)in each subjects' fecal sample and use those measures for AvBrM andAvBrH, instead of measuring them from the subject's breath.)

6) Use a software agent to determine dependency of increased frequencyof Events, zl (as the dependent variable), with the independentvariables being: Markers1-x; GeneExp1-x; VOCsLvL1-x; AvBrM; AvBrH;wherein all independent variables are determined across all testsubjects; using a software agent which (i) determines correlation of zlwith each independent variable using a univariate hypothesis test, wherethe null hypothesis is “the presence of this marker, or this level ofgene expression or greater, or this level of volatile organic compoundsor greater, or these levels of hydrogen and methane or greater, are notassociated with zl”; where such markers are designated Md, such geneexpression levels are designated GEd, such levels of organic compoundsare designated VOCAd; such average levels of methane are designated;BrMd, and such average levels of hydrogen are designated BrHd (ii)performs a multivariate regression model of all possible combinations ofthe independent variables Markers1-x; GeneExp1-x; and VOCsLvL1-x, AvBrM;AvBrH with substantially the same null hypothesis as in step (i) butwhere the word “or” is “and”; to represent the combination ofindependent variables modeled, where the following formula representsthis multivariate regression model:

zl=

(Markers1-x; GeneExp1-x; VOCsLvL1-x; AvBrM; AvBrH)

Determine the independent variables and combinations thereof where thedependency of increased frequency of Events, zl, is established at aconfidence interval (CI) of at least 95% for the appropriate nullhypothesis noted above in steps (i) and (ii); for markers Md, for geneexpression levels GEd, for levels of organic compounds VOCAd; for levelsof methane AvBrM; and for levels of hydrogen AvBrH.

7) Use a software agent to determine dependency of increased frequencyof Events, zl (as the dependent variable), with the dependent variablebeing a diet with consumption of a quantity, q, of FODMAP or otherspecified (non-preferred) foods above a threshold, Th, consumed in aperiod of time, t, as represented by the formula:

zl=

(q(Th)(t)), where such consumption is designated “qTht”;

where the dependency of increased frequency of Events, zl, isestablished at a confidence interval (CI) of at least 95% (where thenull hypothesis is: “consumption of a quantity, q, of FODMAP or othernon-preferred foods above a threshold, Th, consumed in a period of time,t, are not associated with increased frequency of Events, z”;

8) Use a software agent to determine dependency of decreased frequencyof Events (as the dependent variable, Zr), with the independent variablebeing a level of volatile organic compounds in Table B (“B-VOCsLvL1-x”)above a threshold associated with normal subjects or remission (seespecification), where the B-VOCsLvL can be measured from gas associatedwith the fecal sample, and where such dependency is established at aconfidence interval (CI) of at least 95% (where the null hypothesis is:“Levels of B-VOCsLvLs above this threshold are not associated withdecreased frequency of Events, Zr”; where such levels are designatedVOCBd), where the following formula represents this step 8:

Zr=

(BVOCsLvL1-x)

9) Use a software agent to determine correlation between consumption ofqTht and levels of VOCBd (below the threshold):

qTht=

(VOCBd)

at a confidence interval (CI) of at least 95%, by using as a nullhypothesis: “consumption of qTht does not correlate with levels of VOCBdbelow the threshold.”

10) Use a software agent to determine correlation between consumption ofqTht and levels of VOCAd (above the threshold):

qTht=

(VOCAd)

at a confidence interval (CI) of at least 95%, by using as a nullhypothesis: “consumption primarily of qTht does not correlate withlevels of VOCAd above the threshold.”

11) Use a software agent to determine correlation between consumption ofqTht and levels of methane BrMd (above the threshold):

qTht=

(BrMd)

at a confidence interval (CI) of at least 95%, by using as a nullhypothesis: “consumption primarily of qTht does not correlate withlevels of BrMd above the threshold.”

12) Use a software agent to determine correlation between consumption ofqTht and levels of hydrogen BrHd (above the threshold):

qTht=

(BrHd)

at a confidence interval (CI) of at least 95%, by using as a nullhypothesis: “consumption primarily of qTht does not correlate withlevels of BrHd above the threshold.”

13) Based on an individual X's profile including dietary restrictions,and the diet determined in steps 7 and 9 to minimize Events, formulate apersonalized diet (“Diet”) for individual X to minimize Events in viewof the individual X profile and dietary restrictions, and provide theDiet to individual X on the wireless device;

14) Monitor individual X's food items consumed and frequency of Events,based on entries in individual X's wireless device;

15) Confirm or refute for individual X correlation of Diet withdecreased frequency of Events (“Zr”) as compared with Evsbaseline; i.e.,individual X following the Diet results in (Evsbaseline)>frequency(Events);

16) Confirm or refute for individual X, a decreased frequency of Events(Zr) as compared with Evsbaseline; for each of: gene expressionlevels<GEd, VOCsLvL<VOCAd, and B-VOCsLvL>VOCBd; AvBrM<BrMd; AvBrH<BrHd;and an increased frequency of Events (zl) as compared with Evsbaseline(i.e., frequency (Events)>(Evsbaseline)) with the presence of markers Mdin the sample;

17) Confirm or refute for individual X that consumption of qThtcorrelates with levels of VOCAd (above the threshold) (Correlation A);

18) Confirm or refute for individual X that consumption of qThtcorrelates with levels of VOCBd (below the threshold) (Correlation B);

19) Confirm or refute for individual X that consumption of qThtcorrelates with levels of BrMd (above the threshold) (Correlation C);

20) Confirm or refute for individual X that consumption of qThtcorrelates with levels of BrHd (above the threshold) (Correlation D);

21) If individual X shows a decreased frequency of Events (Zr) where anyof the following are true: VOCsLvL<VOCAd; B-VOCsLvL>VOCBd; AvBrM<BrMd;AvBrH<BrHd; and markers Md are absent; and if any of Correlations Athrough D are established for individual X, but individual X does notshow decreased frequency of Events by following the Diet, messageindividual X to do one or more of: enter all food consumed, accuratelyreport of food intake or do not enter foods erroneously; and ifindividual X continues to not show decreased frequency of Events byfollowing the Diet, send messages to individual X to sequentiallyeliminate particular foods typically consumed until either all foodsconsumed are eliminated and deemed not causative, or foods associatedwith the failure to decrease frequency of Events zl are identified(i.e., which foods fail to alleviate symptoms); and

22) If individual X shows decreased frequency of Events when followingthe Diet, and shows increased frequency of Events when not following theDiet: message individual X about (i) the Diet and/or the importance ofconsistently following the Diet and (ii) specifying in the messages howto conform individual X's food intake to the Diet, based on the foodintake reported by individual X during periods when there was increasedfrequency of Events (see flow-chart B examples).

The steps 1-22 above and Figs. FIGS. 5A, 5B provides a rigorous analysisof a number of data points from test subjects, with the objective toprovide an optimized diet for an individual with IBD. It shows further,how to construct messages for the individual to adhere to or optimizethe diet to reduce symptoms of IBD. FIGS. 6A, 6B summarize steps 1-22 inequation form.

Another set of data points can also be analyzed and then applied to anindividual, in addition to those in FIGS. 5A, 5B and steps 1-22 above;as shown in FIGS. 6A, 6B. For the steps in FIGS. 7A, 7B (and the stepsin 1a et seq below) it is assumed that the correlation in step 7 above,i.e., zl=

(q(Th)(t)), had been established in test subjects.

These data points relate to the composition of the gut's bacteria, alsoknown as the microbiome. The full explanation of the flow chart in FIGS.7A, 7B is as follows in steps 1a to 9a.

1a) Obtain details of digestive health of each test subject: healthprofiles, and past and present digestive ailments i.e.: whethersuffering from IBS, IBD, frequent diarrhea, high frequency flatulence,high frequency bowel movements (“Events” or “symptoms”), and also thebaseline frequency of Events, (“Evsbaseline”);

2a) Perform baseline fecal sample collection for test subjects toinitially determine: (i) concentrations of Bifidobacteria,Lactobacillus, Faecalibacterium prausnitzii and Propionibacteriaceae(“Beneficial Microbes”); (ii) concentrations of Bacteroides fragilis,Ruminococcaceae and Clostridium (“Detrimental Microbes”); and (iii)presence of any mutants of Beneficial Microbes or Detrimental Microbes(based on presence of any Markers1-x) which are associated with Zr(referred to as “Mutants” and including “Md”).

3a) Monitor diet of each test subject using a wireless device whichallows input of all food items and quantity consumed; withrecommendations on screen for low FODMAP foods, and preferably showingcarbohydrate content and glycemic Index, fat and protein content, glutenlevels, for each meal or for each food item;

4a) Collect fecal samples at intervals for each test subject: andmonitor concentrations of Beneficial Microbes and Detrimental Microbesand Mutants, during each collection period;

5a) Use a software agent to determine correlation of qTht with decreasedconcentrations of Beneficial Microbes and increased concentration ofDetrimental Microbes and absence of Mutants; and using a univariatehypothesis test, where the null hypothesis is “qTht is not associatedwith increased concentrations of Beneficial Microbes and decreasedconcentration of Detrimental Microbes and absence of Mutants;” at aconfidence interval (CI) of at least 95% for the null hypothesis;

6a) Use a software agent to determine correlation of increased frequencyof events, zl, with decreased concentrations of Beneficial Microbes andincreased concentration of Detrimental Microbes and/or presence ofMutants.

7a) If the correlation in step 5a or 6a is established at a confidenceinterval (CI) of at least 95% for the null hypothesis, confirm or refutefor individual X the correlation between qTht and/or zl with decreasedconcentrations of Beneficial Microbes and increased concentration ofDetrimental Microbes and presence of Mutants;

8a) if the correlation in step 5a is established for individual X, butindividual X reports consuming only low FODMAP or other recommendedfoods and fecal samples do not show increased concentrations ofBeneficial Microbes and decreased concentration of Detrimental Microbesand absence of Mutants; send messages to individual X to sequentiallyeliminate particular foods typically consumed until either all foodsconsumed are eliminated and deemed not causative, or foods associatedwith the failure to increase concentrations of Beneficial Microbes anddecrease concentration of Detrimental Microbes reduce Mutants areidentified; and

9a) If individual X shows increased concentrations of BeneficialMicrobes and decreased concentration of Detrimental Microbes whenfollowing a low FODMAP or other recommended diet, and shows the oppositewhen not following a low FODMAP or other recommended diet: messageindividual X about (i) the importance of consistently following the lowFODMAP or other recommended diet and (ii) specifying in the messages howto conform individual X's food intake to the low FODMAP or otherrecommended diet, based on the food intake reported by individual X.

Essentially the same systems as above and in FIGS. 5A-7B could also beused to identify supplements, prescription drugs, exercise ormanipulation regimes, or other treatment methods—instead of or inaddition to relying on consuming a low FODMAP diet to reduce Events. Tofind such other treatment methods, the same steps 1-22 and 1a to 9aabove (as shown in the flow charts in FIGS. 5A, 5B and 7A, 7B,respectively) can be performed, but with the “other treatment method”being tested substituted for the “low FODMAP diet.” For example, insteps 3 or 3a above, where the treatment tested was a drug, one wouldmonitor each test subject using a wireless device which allows input ofthe drug dosage consumed. In steps 7 and 5a, one would substitute thedrug dosage consumed as the dependent variable. For a drug dosagedetermined in steps 7 and 8 to minimize Events, that drug dosage can betested by an individual (“individual X”) to determine if it is effectivefor the individual in reducing Events. The relationship between the drugconsumption and the various indicators in step 16, i.e., “geneexpression levels<GEd, VOCsLvL<VOCAd, and B-VOCsLvL>VOCBd; AvBrM<BrMd;AvBrH<BrHd” or between the drug consumption and increased concentrationsof Beneficial Microbes and decreased concentration of DetrimentalMicrobes and Mutants in step 5a, can also be determined as additionalverification that the drug is effective for reducing Events. Asupplement would be tested and verified in the same manner, as could anytype of exercise or manipulation regimes, or other treatment methods.

Where the drug, supplement or other treatment method was shown to reduceEvents for individual X, they could be messaged to adhere to thetreatment when any of the indicators in step 16 or 5a indicated onewould expect increased Events.

FIGS. 6A, 6B outline another related embodiment, in equation form, wherea genetic marker or gene expression level is determined to predisposetest subjects to IBD or Events in test subjects, after going through thesteps 1 to 12 above; one can go through steps 13 to 22 above for anindividual Y with the marker or gene expression level, and determine ifincreased frequency of Events is dependent on qTht. The same treatmentin steps 21 and 22 can be used, if so. If not, one can substitute adrug, supplement or another therapy for qTht for an individual(individual Y), and if determined to be effective in ameliorating IBD orreducing frequency of Events, perform similar monitoring of individualY's adherence to the treatment regimen, by monitoring the sameindicators as in steps 13 to 20 and/or 5a and 6a. Again, where theseindicators indicate individual Y is not adhering to the treatmentregime, messages can be sent instructing adherence, and the importanceof doing so. Again, the various indicators (like VOCsLvL1-x;B-VOCsLvL1-x; AvBrM; AvBrH) can also serve as a verification ofindividual Y's adherence to the treatment regime, and whether individualY is truthfully reporting compliance with the treatment regime. Messagescan be sent about the importance of compliance with the treatment regimewhen the indicators predict an increase in frequency of Events; whetheror not such increase is reported by individual Y.

In another related embodiment, it can be determined for an individual(individual Z) if any gene expression levels correlate with a particulardiet, or with consumption of any drug, supplement or other therapy, andwith increased or reduced frequency of Events. In such case, the geneexpression level can be used to monitor compliance by individual Z withthe diet or the other treatment regime, as described above.

Another related embodiment is to standardize messaging to test subjectsand individuals. The first step in message selection, for querying thesubject's condition and for instructing treatment, is establishing,initially, a testing a set of messages for each domain, and verifyingthat the messages are not confusing or ambiguous or difficult tounderstand and correctly answer. This is accomplished by determiningCronbach's Alphas for a set of messages sent to users. For a quantitywhich is a sum of K, components (also called testlets or items)X=Y1+Y2+Y3 . . . YK, Cronbach's alpha is defined as:

$\alpha = {\left( \frac{k}{k - 1} \right)\left( {1 - \frac{\sum\limits_{i = 1}^{k}\; \sigma_{y_{i}}^{2}}{\sigma_{x}^{2}}} \right)}$

where σ² _(X) is the variance of the observed total scores fromsubjects/individuals and where σ² _(Yi) is the variant of component ifor the responding subjects/individuals.

To apply Cronbach's alpha in formulating a database of clear questions,for each test subject and user, one compares the sum of items' variance(through the whole set of responses from test subjects and users) to thevariance of the sum of the total test scores.

If the sum of items' variance is significantly greater than the varianceof the sum of the total test scores, it means that the portion of theerrors resulting from misinterpretation, confusion, misunderstanding orrelated reasons is large, and the status the questions are designed todetermine is unreliable. In such cases, the questions need to bereformulated and the new questions need to be tested for reliabilityusing Cronbach's alpha again.

The invention has been described broadly and generically herein. Each ofthe narrower species and subgeneric groupings falling within the genericdisclosure also form part of the invention. The terms and expressionsthat have been employed are used as terms of description and not oflimitation, and there is no intent in the use of such terms andexpressions to exclude any equivalent of the features shown anddescribed or portions thereof, but it is recognized that variousmodifications are possible within the scope of the invention as claimed.Thus, it will be understood that although the present invention has beenspecifically disclosed by preferred embodiments and optional features,modification and variation of the concepts herein disclosed may beresorted to by those skilled in the art, and that such modifications andvariations are considered to be within the scope of this invention asdefined by the appended claims.

1-20. (canceled)
 21. A method of treating one or more of the conditionsof IBS, IBD, frequent diarrhea, high frequency flatulence or highfrequency bowel movements by finding an avoidance diet eliminatingnon-preferred foods to minimize at least one symptom of said conditionsand instructing adherence to the avoidance diet by an individual, themethod comprising: a) finding an avoidance diet by: A) assaying breathor fecal samples from the test subjects wherein the assaying determinesone or more of: methane levels designated BrM and hydrogen levelsdesignated BrH, wherein BrH and BrM are transmitted to a server whendetermined from the subjects' breath; B) identifying a correlationbetween BrM or BrH and the at least one symptom in the test subjects; C)identifying any foods associated with generating or worsening of the atleast one symptom in the test subjects, and designating such foods asnon-preferred foods; and D) identifying a correlation between avoidanceof certain of the non-preferred foods by the test subjects and BrM orBrH; and b) determining in the individual if there is a correlation inthe individual between avoidance of said certain of the non-preferredfoods by the individual and alleviating the at least one symptom in theindividual and, if said correlation is established, instructingadherence to the avoidance diet by sending the individual instructionsto avoid said certain of the non-preferred foods.
 22. The method ofclaim 21 further including: A) assaying fecal samples from the group oftest subjects for one or more of: (i) DNA and/or RNA markers associatedwith the test subjects having the at least one symptom, but not inwild-type, designated Markers1-x; (ii) gene expression of any candidategenes whose expression is elevated or decreased in the test subjects butnot in a population which does not exhibit the at least one symptom,designated GeneExp1-x; (iii) concentrations, in samples taken from asubset of the test subjects of a first set of volatile organiccompounds, designated VOCsLvL; (iv) concentrations, in samples takenfrom the subset of test subjects, of a second set of volatile organiccompounds, designated B-VOCsLvL; and (v) gut concentrations, in samplestaken from the subset of test subjects of one or more of the bacteria:Bifidobacteria, Lactobacillus, Faecalibacterium prausnitzii,Propionibacteriaceae, Bacteroides fragilis, Ruminococcaceae andClostridium; B) identifying a correlation between one or more of:Markers1-x, GeneExp1-x, VOCsLvL and gut concentrations of one or more ofsaid bacteria; with the at least one symptom in the test subjects; andC) identifying a correlation between avoidance of certain of thenon-preferred foods by the test subjects and one or more of: Markers1-x,GeneExp1-x, VOCsLvL and gut concentrations of one or more of saidbacteria.
 23. The method of claim 21 wherein BrM or BrH are determinedfrom analysis of breath gas samples taken while the test subjects areexhibiting the at least one symptom.
 24. The method of claim 22 whereinone or more of BrM, BrH, Markers1-x, GeneExp1-x, VOCsLvL, B-VOCsLvL andgut concentrations of said bacteria are taken from fecal samples whilethe test subjects are exhibiting the at least one symptom.
 25. Themethod of claim 22 further including determining in said individual ifthere is a correlation between alleviating or worsening of the at leastone symptom and one or more of: Markers1-x, GeneExp1-x, VOCsLvL,B-VOCsLvL, BrM, BrH, and gut concentrations of one or more of saidbacteria.
 26. The method of claim 22 wherein if one or more ofGeneExp1-x, VOCsLvL, B-VOCsLvL, BrM, BrH, and gut concentrations of oneor more of the bacteria don't correlate with avoidance of said certainof the non-preferred foods by the individual as in the test subjects,thereby indicating food entry errors by the individual, then theindividual is immediately again sent the instructions.
 27. The method ofclaim 26 wherein the individual is sent an instruction to input all fooditems and quantity consumed.
 28. The method of claim 21 furtherincluding instructing the individual, when the individual has worseningof the at least one symptom, to sequentially eliminate consumption ofparticular foods to identify consumed foods which result in failure toalleviate the at least one symptom.
 29. The method of claim 26 furtherincluding sending the individual a message relating to the importance ofconsistently avoiding said certain of the non-preferred foods.
 30. Themethod of claim 26 further including sending the individual a messageabout how to conform the individual's food intake to avoid said certainof the non-preferred foods, based on the food intake reported by theindividual during periods when there was lack of alleviation of the atleast one symptom.
 31. The method of claim 1 wherein said non-preferredfoods are low in fermentable sugars.
 32. The method of claim 22 whereinthe VOCsLvL are selected from the group consisting of: Butanoic acid,ethyl ester; Propanoic acid, methyl ester;1-Methyl-2-(1-methylethyl)-benzene; Butanoic acid, butyl ester; Butanoicacid, propyl ester; Hexanoic acid, methyl ester; Propanoic acid, propylester; Acetic acid, butyl ester; Butanoic acid, 3-methyl-, butyl ester;Propanoic acid, butyl ester; Cyclohexanecarboxylic acid, ethyl ester;Butanoic acid, 2-methyl-, propyl ester; Ethanoic acid, ethyl ester;Pentanoic acid, 4-methyl; Acetic acid, pentyl ester; Pentanoic acid,butyl ester; Butanoic acid, 3-methyl-, propyl ester;Cyclohexanecarboxylic acid, propyl ester; 6-Methyl-5-hepten-2-one;Propanoic acid, 3-methyl-butyl ester; Ethanoic acid, 3-methyl-1-butylester; Cyclohexanecarboxylic acid, butyl ester; Benzoic acid,2-hydroxy-, methyl ester; Pentanoic acid, 4-methyl-, pentyl ester;Butanoic acid, 3-methyl-, methyl ester; Thiopivalic acid;5-Methyl-2-(1-methylethyl)-cyclohexanone; and 4-Methyl-1-Indole.
 33. Themethod of claim 22 wherein the B-VOCsLvL are selected from the groupconsisting of: 2-Heptanone; 2-Methylpropanal; 3-Methylbutanoic acid;Undecane; 3-Methylbutanal; 2-Methylpropanoic acid; 2-Methyl-1-propanol;1R-a-Pinene; 2-Penhifizran; Methoxy-phenyl-oxime; and 2-Methylfuran. 34.The method of claim 22 wherein the VOCsLvL and B-VOCsLvL are determinedin gas from the fecal sample.
 35. A method of treating one or more ofthe conditions of IBS, IBD, frequent diarrhea, high frequency flatulenceor high frequency bowel movements by finding an avoidance dieteliminating non-preferred foods to minimize at least one symptom of saidconditions and instructing adherence to the avoidance diet by anindividual, the method comprising: a) finding an avoidance diet by: A)assaying fecal samples from a group of test subjects exhibiting the atleast one symptom, for one or more of: (i) concentrations of a first setof volatile organic compounds designated VOCsLvL; (ii) concentrations ofa second set of volatile organic compounds designated B-VOCsLvL; and(iii) gut concentrations of one or more of the bacteria: Bifidobacteria,Lactobacillus, Faecalibacterium prausnitzii, Propionibacteriaceae,Bacteroides fragilis, Ruminococcaceae and Clostridium; B) identifying acorrelation between one or more of VOCsLvL, B-VOCsLvL, gutconcentrations of one or more of said bacteria and the at least onesymptom in the test subjects; C) identifying any foods associated withthe at least one symptom in the test subjects and designating such foodsas non-preferred foods; and D) identifying a correlation betweenavoidance of certain of the non-preferred foods by the test subjects andone or more of VOCsLvL, B-VOCsLvL and gut concentrations of one or moreof said bacteria; and b) determining in the individual if there is afirst correlation in the individual between avoidance of said certain ofthe non-preferred foods by the individual and alleviating the at leastone symptom in the individual and, determining in said individual, ifthere is a second correlation between alleviating or worsening of the atleast one symptom and one or more of: VOCsLvL, B-VOCsLvL and gutconcentrations of one or more of the bacteria; and if said first orsecond correlation is established, instructing adherence to theavoidance diet by sending the individual instructions to avoid saidcertain of the non-preferred foods.
 36. The method of claim 35 furtherincluding: assaying breath samples from the test subjects exhibiting theat least one symptom, wherein the assaying determines one or more of:methane levels designated BrM and hydrogen levels designated BrH,wherein BrH and BrM are transmitted to a server; identifying acorrelation between BrH or BrM and the at least one symptom in the testsubjects; identifying a correlation between avoidance of certain of thenon-preferred foods by the test subjects and BrH or BrM; determining inthe individual if there is a third correlation between alleviating orworsening of the at least one symptom and BrH or BrM; and if said thirdcorrelation is established, instructing adherence to the avoidance dietby sending the individual instructions to avoid said certain of thenon-preferred foods.
 37. The method of claim 36 wherein if one or moreof VOCsLvL, B-VOCsLvL, BrM, BrH and gut concentrations of one or more ofthe bacteria don't correlate with avoidance of said certain of thenon-preferred foods by the individual as in the test subjects, therebyindicating food entry errors by the individual, then the individual isimmediately again sent the instructions.
 38. The method of claim 35wherein the individual is sent an instruction to input all food itemsand quantity consumed.
 39. The method of claim 35 further includinginstructing the individual, when the individual has worsening of atleast one symptom, to sequentially eliminate consumption of particularfoods to identify consumed foods which result in failure to alleviatethe at least one symptom.
 40. The method of claim 36 wherein one or moreof BrM, BrH, Markers1-x, GeneExp1-x, VOCsLvL, B-VOCsLvL and gutconcentrations of said bacteria are taken while the test subjects areexhibiting the at least one symptom.